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The DIADEM Data Sets: Representative Light Microscopy Images of Neuronal Morphology to Advance Automation of Digital Reconstructions

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Abstract

The comprehensive characterization of neuronal morphology requires tracing extensive axonal and dendritic arbors imaged with light microscopy into digital reconstructions. Considerable effort is ongoing to automate this greatly labor-intensive and currently rate-determining process. Experimental data in the form of manually traced digital reconstructions and corresponding image stacks play a vital role in developing increasingly more powerful reconstruction algorithms. The DIADEM challenge (short for DIgital reconstruction of Axonal and DEndritic Morphology) successfully stimulated progress in this area by utilizing six data set collections from different animal species, brain regions, neuron types, and visualization methods. The original research projects that provided these data are representative of the diverse scientific questions addressed in this field. At the same time, these data provide a benchmark for the types of demands automated software must meet to achieve the quality of manual reconstructions while minimizing human involvement. The DIADEM data underwent extensive curation, including quality control, metadata annotation, and format standardization, to focus the challenge on the most substantial technical obstacles. This data set package is now freely released (http://diademchallenge.org) to train, test, and aid development of automated reconstruction algorithms.

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Information Sharing Statement

The DIADEM data sets are freely available at http://diademchallenge.org.

Acknowledgements

The corresponding author’s lab is supported in part by NIH R01 grant 39600. Todd A. Gillette is acknowledged for help and advice throughout the DIADEM data set organization process. Figure 4 illustration was created with V3D (http://penglab.janelia.org/proj/v3d).

Author information

Author notes

  1. Alison J. Canty

    Present address: School of Medicine, University of Tasmania, Hobart, TAS, Australia

  2. Marjolein Snippe

    Present address: Blizard Institute of Cell and Molecular Science, Queen Mary University of London, London, UK

Authors and Affiliations

  1. Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA

    Kerry M. Brown & Giorgio A. Ascoli

  2. Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA

    Germán Barrionuevo

  3. MRC Clinical Sciences Centre, Imperial College London, London, UK

    Alison J. Canty, Vincenzo De Paola & Marjolein Snippe

  4. Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA

    Judith A. Hirsch

  5. Division of Neurobiology, MRC Laboratory of Molecular Biology, Cambridge, UK

    Gregory S. X. E. Jefferis

  6. Department of Biological Sciences, James H. Clark Center for Biomedical Engineering and Sciences, Stanford University, Stanford, CA, USA

    Ju Lu

  7. Department of Systems Neurophysiology, Tokyo Medical and Dental University School of Medicine, Tokyo, Japan

    Izumi Sugihara

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Correspondence to Giorgio A. Ascoli.

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Brown, K.M., Barrionuevo, G., Canty, A.J. et al. The DIADEM Data Sets: Representative Light Microscopy Images of Neuronal Morphology to Advance Automation of Digital Reconstructions. Neuroinform 9, 143–157 (2011). https://doi.org/10.1007/s12021-010-9095-5

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